MRI-CropNet for Automated Cropping of Prostate Cancer in Magnetic Resonance Imaging
Author:
Funder
Ministry of Human Resource Development (MHRD), Govt. of India
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11277-024-11335-5.pdf
Reference48 articles.
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2. Mohler, J., Bahnson, R. R., Boston, B., Busby, J. E., D’Amico, A., Eastham, J. A., Enke, C. A., George, D., Horwitz, E. M., Huben, R. P., & Kantoff, P. (2010). Prostate cancer. Journal of the National Comprehensive Cancer Network., 8(2), 162–200.
3. Goldenberg, S. L., Nir, G., & Salcudean, S. E. (2019). A new era: Artificial intelligence and machine learning in prostate cancer. Nature Reviews Urology, 16(7), 391–403.
4. Lu, Z., Zhao, M., & Pang, Y. (2020). CDA-net for automatic prostate segmentation in MR images. Applied Sciences, 10(19), 6678.
5. Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118.
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